GTSE1: A potential prognostic and diagnostic biomarker in various tumors including lung adenocarcinoma.

OBJECTIVE: This research was aimed to comprehensively investigate the expression levels, diagnostic and prognostic implications, and the relationship with immune infiltration of G2 and S phase-expressed-1 (GTSE1) across 33 tumor types, including lung adenocarcinoma (LUAD), through gene expression profiling. METHODS: GTSE1 mRNA expression data together with clinical information were acquired from Xena database of The Cancer Genome Atlas (TCGA), ArrayExpress, and Gene Expression Omnibus (GEO) database for this study. The Wilcoxon rank-sum test was used to detect differences in GTSE1 expression between groups. The ability of GTSE1 to accurately predict cancer status was evaluated by calculating the area under the curve (AUC) value for the receiver operating characteristic curve. Additionally, we investigated the predictive value of GTSE1 in individuals diagnosed with neoplasms using univariate Cox regression analysis as well as Kaplan-Meier curves. Furthermore, the correlation between GTSE1 expression and levels of immune infiltration was assessed by utilizing the Tumor Immune Estimate Resource (TIMER) database to calculate the Spearman rank correlation coefficient. Finally, the pan-cancer analysis findings were validated by examining the association between GTSE1 expression and prognosis among patients with LUAD. RESULTS: GTSE1 exhibited significantly increased expression levels in a wide range of tumor tissues in contrast with normal tissues (p < 0.05). The expression of GTSE1 in various tumors was associated with clinical features, overall survival, and disease-specific survival (p < 0.05). In immune infiltration analyses, a strong correlation of the level of immune infiltration with the expression of GTSE1 was observed. Furthermore, GTSE1 demonstrated good discriminative and diagnostic value for most tumors. Additional experiments confirmed the relationship between elevated GTSE1 expression and unfavorable prognosis in individuals diagnosed with LUAD. These findings indicated the crucial role of GTSE1 expression level in influencing the development and immune infiltration of different types of tumors. CONCLUSIONS: GTSE1 might be a potential biomarker for the prognosis of pan-cancer. Meanwhile, it represented a promising target for immunotherapy.

The causal relationship between COVID-19 and ten esophageal diseases: a study utilizing Mendelian randomization.

Background: Clinical signs of dysphagia, pancreatic achalasia, and esophagitis have been reported in patients with COVID-19. However, the causal relationship between COVID-19 and esophageal diseases is not clear. Therefore, we utilized Mendelian randomization to explore the potential association between COVID-19 and esophageal diseases. Methods: The summary statistics for a Genome-wide association study (GWAS) were obtained from The COVID-19 Host Genetics Initiative, encompassing four types of COVID-19 as exposure: severe COVID-19, hospitalized COVID-19 versus ambulatory COVID-19, hospitalized COVID-19 versus uninfected, and confirmed COVID-19. Additionally, summary statistics for ten esophageal diseases as outcomes were sourced from the GWAS Catalog and FinnGen databases. Univariate Mendelian randomization (MR) analysis was utilized to thoroughly investigate and validate the potential causal association between COVID-19 and various esophageal conditions, including esophageal varices, Barrett's esophagus, esophagitis, esophageal obstruction, esophageal ulcer, esophageal perforation, gastroesophageal reflux, congenital esophageal malformations, benign esophageal tumors, and esophageal adenocarcinoma. Results: An inverse variance-weighted (IVW) model was utilized for univariate Mendelian randomization (MR) analysis, which revealed that genetic liability in patients with confirmed COVID-19 was associated with esophageal obstruction (OR [95% CI]: 0.5275458 [0.2822400-0.9860563]; p-value = 0.0450699). Furthermore, a suggestive causal association was found between genetic liability and a reduced risk of benign esophageal tumors (OR [95% CI]: 0.2715453 [0.09368493-0.7870724]; p-value = 0.0163510), but with a suggestively increased risk of congenital esophageal malformations (OR [95% CI]: 6.959561 [1.1955828-40.51204]; p-value = 0.03086835). Additionally, genetic liability in hospitalized COVID-19 patients, compared to non-hospitalized COVID-19 patients, was suggestively associated with an increased risk of esophagitis (OR [95% CI]: 1.443859 [1.0890568-1.914252]; p-value = 0.01068201). The reliability of these causal findings is supported by Cochran's Q statistic and the MR-Egger intercept test. Conclusion: The results of this study suggest the existence of a causal relationship between COVID-19 and esophageal diseases, highlighting differing risk effects of COVID-19 on distinct esophageal conditions.

A novel prognostic signature of coagulation-related genes leveraged by machine learning algorithms for lung squamous cell carcinoma.

Coagulation-related genes (CRGs) have been demonstrated to be essential for the development of certain tumors; however, little is known about CRGs in lung squamous cell carcinoma (LUSC). In this study, we adopted CRGs to construct a coagulation-related gene prognostic signature (CRGPS) using machine learning algorithms. Using a set of 92 machine learning integrated algorithms, the CRGPS was determined to be the optimal prognostic signature (median C-index = 0.600) for predicting the prognosis of an LUSC patient. The CRGPS was not only superior to traditional clinical parameters (e.g., T stage, age, and gender) and its commutative genes but also outperformed 19 preexisting prognostic signatures for LUSC on predictive accuracy. The CRGPS score was positively correlated with poor prognoses in patients with LUSC (hazard ratio > 1, p < 0.05), indicating its suitability as a prognostic marker for this disease. The CRGPS was observed to be inversely correlated with the degree of infiltration of natural killer cells. For some tumors, patients with lower CRGPS scores are more likely to experience enhanced immunotherapy effects (area under the curve = 0.70), which implies that the CRGPS can potentially predict immunotherapy efficacy. A high CRGPS score is predictive of an LUSC patient being sensitive to several drugs. Collectively, these findings indicate that the CRGPS may be a reliable indicator of the prognoses of patients with LUSC and may be useful for the clinical management of such patients.

MMP12 is a Potential Predictive and Prognostic Biomarker of Various Cancers Including Lung Adenocarcinoma.

OBJECTIVE: This study sought to explore the clinical value of matrix metalloproteinases 12 (MMP12) in multiple cancers, including lung adenocarcinoma (LUAD). METHODS: Using >10,000 samples, this retrospective study demonstrated the first pan-cancer analysis of MMP12. The expression of MMP12 between cancer groups and their control groups was analyzed using Wilcoxon rank-sum tests. The clinical significance of MMP12 expression in multiple cancers was assessed using receiver operating characteristic curves, Kaplan-Meier curves, and univariate Cox analysis. A further LUAD-related analysis based on 4565 multi-center and in-house samples was performed to verify the findings regarding MMP12 in pan-cancer analysis partly. RESULTS: MMP12 mRNA is highly expressed in 13 cancers compared to their controls, and the MMP12 protein level is elevated in some of these cancers (e.g., colon adenocarcinoma) (P < .05). MMP12 expression makes it feasible to distinguish 21 cancer tissues from normal tissues (AUC = 0.86). A high MMP12 expression is a prognosis risk factor in eight cancers, such as adrenocortical carcinoma (hazard ratio >1, P < .05). The elevated MMP12 expression is also a prognosis protective factor in breast-invasive carcinoma and colon adenocarcinoma (hazard ratio <1, P < .05). Some pan-cancer findings regarding MMP12 are verified in LUAD-MMP12 expression is upregulated in LUAD at both the mRNA and protein levels (P < .05), has the potential to distinguish LUAD with considerable accuracy (AUC = .91), and plays a risk prognosis factor for patients with the disease (P < .05). CONCLUSIONS: MMP12 is highly expressed in most cancers and may serve as a novel biomarker for the prediction and prognosis of numerous cancers.

Risk factors for one-year mortality following discharge in patients with acute aortic dissection: development and validation of a predictive model in a cross-sectional study.

PURPOSE: This study was aimed to identify the risk factors that influence the mortality risk in patients with acute aortic dissection (AAD) within one year after discharge, and aimed to construct a predictive model for assessing mortality risk. METHODS: The study involved 320 adult patients obtained from the Medical Information Mart for Intensive Care (MIMIC) database. Logistic regression analysis was conducted to identify potential risk factors associated with mortality in AAD patients within one year after discharge and to develop a predictive model. The performance of the predictive model was assessed using the receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). To further validate the findings, patient data from the First Affiliated Hospital of Guangxi Medical University (157 patients) were analyzed. RESULTS: Univariate and multivariate logistic regression analyses revealed that gender, length of hospital stay, highest blood urea nitrogen (BUN_max), use of adrenaline, and use of amiodarone were significant risk factors for mortality within one year after discharge (p < 0.05). The constructed model exhibited a consistency index (C-index) and an area under the ROC curve of 0.738. The calibration curve and DCA demonstrated that these indicators had a good degree of agreement and utility. The external validation results of the model also indicated good predictability (AUC = 0.700, p < 0.05). CONCLUSION: The personalized scoring prediction model constructed by gender, length of hospital stays, BUN_max levels, as well as the use of adrenaline and amiodarone, can effectively identify AAD patients with high mortality risk within one year after discharge.

CDK6 is a novel predictive and prognosis biomarker correlated with immune infiltrates in multiple human neoplasms, including small cell lung carcinoma.

The roles of cyclin-dependent kinase 6 (CDK6) in various cancers, including small cell lung carcinoma (SCLC), remain unclear. Here, 111,54 multi-center samples were investigated to determine the expression, clinical significance, and underlying mechanisms of CDK6 in 34 cancers. The area under the curve (AUC), Cox regression analysis, and the Kaplan-Meier curves were used to explore the clinical value of CDK6 in cancers. Gene set enrichment analysis and correlation analysis were performed to detect potential CDK6 mechanisms. CDK6 expression was essential in 24 cancer cell types. Abnormal CDK6 expression was observed in 14 cancer types (e.g., downregulated in breast invasive carcinoma; p < 0.05). CDK6 allowed six cancers to be distinguished from their controls (AUC > 0.750). CDK6 expression was a prognosis marker for 13 cancers (e.g., adrenocortical carcinoma; p < 0.05). CDK6 was correlated with several immune-related signaling pathways and the infiltration levels of certain immune cells (e.g., CD8+ T cells; p < 0.05). Downregulated CDK6 mRNA and protein levels were observed in SCLC (p < 0.05, SMD = - 0.90). CDK6 allowed the identification of SCLC status (AUC = 0.91) and predicted a favorable prognosis for SCLC patients (p < 0.05). CDK6 may be a novel biomarker for the prediction and prognosis of several cancers, including SCLC.

The mitotic cell cycle-associated nomogram predicts overall survival in lung adenocarcinoma.

BACKGROUND: This study aimed to develop a prognostic model for lung adenocarcinoma (LUAD) associated with mitotic cell cycle. The model will predict the probability of survival at different time points and serve as a reference tool to evaluate the effectiveness of LUAD treatment. METHODS: A cohort of 442 patients with LUAD from the gene expression omnibus (GEO) database was randomly divided into a training group (n = 299) and a validation group (n = 99). The least absolute shrinkage and selection operator (LASSO)-COX algorithm was used to reduce the number of predictors based on the clinicopathological and RNA sequencing data to establish mutant characteristics that could predict patient survival. Additionally, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set variation analysis (GSVA), and gene set enrichment analysis (GSEA) analyses were conducted on the mutant characteristics. The performance of the developed nomogram was evaluated using calibration curves and the C-index. RESULTS: The mutant characteristics had prognostic value for LUAD and acted as an independent prognostic factor. The mutant characteristics profile derived from the LASSO-COX algorithm demonstrated a significant association with overall survival in patients with LUAD. Functional annotation based on the mutant score, its involvement in the phase transition of the mitotic cell cycle, and its regulatory processes. The nomogram, which combined the mutant score with clinical factors associated with prognosis, showed robust accuracy in both the training and validation groups. CONCLUSION: This study presents the first individualized model that establishes a mutant score for predicting survival in LUAD. This model can be used as a predictive tool for determining 1-, 2-, 3-, and 5-year survival probabilities in patients with LUAD.

ITGB4 Serves as an Identification and Prognosis Marker Associated with Immune Infiltration in Small Cell Lung Carcinoma.

Integrin beta 4 (ITGB4) is a vital factor for numerous cancers. However, no reports regarding ITGB4 in small cell lung carcinoma (SCLC) have been found in the existing literature. This study systematically investigated the expression and clinical value of ITGB4 in SCLC using multi-center and large-sample (n = 963) data. The ITGB4 expression levels between SCLC and control tissues were compared using standardized mean difference and Wilcoxon rank-sum test. The clinical significance of the gene in SCLC was observed using Cox regression and Kaplan-Meier curves. ITGB4 is overexpressed in multiple cancers and represents significant value in distinguishing among cancer samples (AUC = 0.91) and predicting the prognoses (p < 0.05) of patients with different cancers. In contrast, decreased ITGB4 mRNA expression was determined in SCLC (SMD < 0), and this finding was further confirmed at protein levels using in-house specimens (p < 0.05). This decrease in expression may be attributed to the regulatory role of estrogen receptor 1. ITGB4 may participate in the progression of SCLC by affecting several signaling pathways (e.g., tumor necrosis factor signaling pathway) and a series of immune cells (e.g., dendritic cells) (p < 0.05). The gene may serve as a potential marker for predicting the disease status (AUC = 0.97) and prognoses (p < 0.05) of patients with SCLC. Collectively, ITGB4 was identified as an identification and prognosis marker associated with immune infiltration in SCLC.

MMP12 serves as an immune cell-related marker of disease status and prognosis in lung squamous cell carcinoma.

Background: Worldwide, lung squamous cell carcinoma (LUSC) has wreaked havoc on humanity. Matrix metallopeptidase 12 (MMP12) plays an essential role in a variety of cancers. This study aimed to reveal the expression, clinical significance, and potential molecular mechanisms of MMP12 in LUSC. Methods: There were 2,738 messenger RNA (mRNA) samples from several multicenter databases used to detect MMP12 expression in LUSC, and 125 tissue samples were validated by immunohistochemistry (IHC) experiments. Receiver operator characteristic (ROC) curves, Kaplan-Meier curves, and univariate and multivariate Cox regression analyses were used to assess the clinical value of MMP12 in LUSC. The potential molecular mechanisms of MMP12 were explored by gene enrichment analysis and immune correlation analysis. Furthermore, single-cell sequencing was used to determine the distribution of MMP12 in multiple tumor microenvironment cells. Results: MMP12 was significantly overexpressed at the mRNA level (p < 0.05, SMD = 3.13, 95% CI [2.51-3.75]), which was verified at the protein level (p < 0.001) by internal IHC experiments. MMP12 expression could be used to differentiate LUSC samples from normal samples, and overexpression of MMP12 itself implied a worse clinical prognosis and higher levels of immune cell infiltration in LUSC patients. MMP12 was involved in cancer development and progression through two immune-related signaling pathways. The high expression of MMP12 in LUSC might act as an antigen-presenting cell-associated tumor neoantigen and activate the body's immune response. Conclusions: MMP12 expression is upregulated in LUSC and high expression of MMP12 serves as a risk factor for LUSC patients. MMP12 may be involved in cancer development by participating in immune-related signaling pathways and elevating the level of immune cell infiltration.

Gene S-phase kinase associated protein 2 is a novel prognostic marker in human neoplasms.

BACKGROUND: Neoplasms are a series of diseases affecting human health. Prognostic and tumor status-related markers for various tumors should be identified. METHODS: Based on 19,515 samples from multiple sources, for the first time, this study provided an overview of gene S-phase kinase associated protein 2 (SKP2) in pan-cancer. Differential SKP2 expression in multiple comparison groups was identified by the Kruskal-Wallis test and Wilcoxon rank-sum test. The prognosis significance of SKP2 in individuals with neoplasm was evaluated through univariate Cox regression analysis and Kaplan-Meier curves. The area under the curve was utilized to detect the accuracy of SKP2 in predicting cancer status. Spearman's rank correlation coefficients were calculated in all correlation analyses. Gene set enrichment analysis was used to identify essential signaling pathways of SKP2 in human neoplasms. RESULTS: The study disclosed the upregulated SKP2 expression in 15 neoplasms and decreased SKP2 expression in three cancers (p < 0.05). The transcription factor Forkhead Box M1 may contribute to the increased expression levels of SKP2 in certain tumors. Over-expressed SKP2 represented a risk factor for the prognosis of most cancer patients (hazard ratio > 1, p < 0.05). SKP2 expression made it feasible to distinguish neoplasm and control tissues of 21 neoplasms (sensitivity = 0.79, specificity = 0.87, area under the curve = 0.90), implying its potential in screening a series of neoplasms. Further, the research revealed the close association of SKP2 expression with DNA methyltransferases, mismatch repair genes, microsatellite instability, tumor mutational burden, neoantigen count, and immunity. CONCLUSIONS: SKP2 plays an essential role in multiple neoplasms and may serve as a marker for treating and identifying these neoplasms.

CEP55: an immune-related predictive and prognostic molecular biomarker for multiple cancers.

BACKGROUND: Centrosomal protein 55 (CEP55) plays a significant role in specific cancers. However, comprehensive research on CEP55 is lacking in pan-cancer. METHODS: In-house and multi-center samples (n = 15,823) were used to analyze CEP55 in 33 cancers. The variance of CEP55 expression levels among tumor and control groups was evaluated by the Wilcoxon rank-sum test and standardized mean difference (SMD). The clinical value of CEP55 in cancers was assessed using receiver operating characteristic (ROC) curves, Cox regression analysis, and Kaplan-Meier curves. The correlations between CEP55 expression and the immune microenvironment were explored using Spearman's correlation coefficient. RESULTS: The data of clustered regularly interspaced short palindromic repeats confirmed that CEP55 was essential for the survival of cancer cells in multiple cancer types. Elevated CEP55 mRNA expression was observed in 20 cancers, including glioblastoma multiforme (p < 0.05). CEP55 mRNA expression made it feasible to distinguish 21 cancer types between cancer specimens and their control samples (AUC = 0.97), indicating the potential of CEP55 for predicting cancer status. Overexpression of CEP55 was correlated with the prognosis of cancer individuals for 18 cancer types, exhibiting its prognostic value. CEP55 expression was relevant to tumor mutation burden, microsatellite instability, neoantigen counts, and the immune microenvironment in various cancers (p < 0.05). The expression level and clinical relevance of CEP55 in cancers were verified in lung squamous cell carcinoma using in-house and multi-center samples (SMD = 4.07; AUC > 0.95; p < 0.05). CONCLUSION: CEP55 may be an immune-related predictive and prognostic marker for multiple cancers, including lung squamous cell carcinoma.

The clinical significance and mechanism of microRNA-22-3p targeting TP53 in lung adenocarcinoma.

BACKGROUND: At present, studies on MircoRNA-22-3p (miR-22-3p) in lung adenocarcinoma use a single method, lack multi-center validation and multi-method validation, and there is no big data concept to predict and validate target genes. OBJECTIVE: To investigate the expression, potential targets and clinicopathological significance of miR-22-3p in lung adenocarcinoma (LUAD) tissues. METHODS: LUAD formalin-fixed paraffin-embedded (FFPE) tumors and adjacent normal lung tissues were collected for real-time quantitative polymerase chain reaction (RT-qPCR). Collect miR-22-3p in LUAD and non-cancer lung tissue from high-throughput datasets, standardized mean difference (SMD) and area under the curve (AUC) of the comprehensive receiver operating curve (summary receiver operating characteristic cure, sROC curve) were calculated. Cell function experiments on A549 cells transfected with LV-hsa-miR-22-3p. Target genes were predicted by the miRwalk2.0 website and the resulting target genes were subjected to Gene Ontology (GO) pathway enrichment analysis and constructed to protein-protein interaction network. Finally, the protein expression level of the key gene TP53 was validated by searching The Human Protein Atlas (THPA) database to incorporate TP53 immunohistochemical results in LUAD. RESULTS: RT-qPCR result from 41 pairs of LUAD and adjacent lung tissues showed that miR-22-3p was downregulated in LUAD (AUC = 0.6597, p= 0.0128). Globally, a total of 838 LUADs and 494 non-cancerous lung tissues were included, and were finally combined into 14 platforms. Compared with noncancerous tissue, miR-22-3p expression level was significantly reduced in LUAD tissue (SMD =-0.32, AUC = 0.72l); cell function experiments showed that miR-22-3p has inhibitory effects on cell proliferation, migration and invasion, and has promotion effect on apoptosis. Moreover, target genes prediction, GO pathway enrichment analysis and PPI network exhibited TP53 as a key gene of target gene of miR-22-3p; at last, a total of 114 high-throughput datasets were included, including 3897 LUADs and 2993 non-cancerous lung tissues, and were finally combined into 37 platforms. Compared with noncancerous tissue, TP53 expression level was significantly increased in LUAD (SMD = 0.39, p< 0.01) and it was verified by the protein expression data from THPA. CONCLUSION: Overexpression of miR-22-3p may inhibit LUAD cell proliferation, migration and invasion through TP53, and promote cell apoptosis.

Prognostic Signature and Discrimination Signature of Lung Adenocarcinoma based on Pyroptosis-Related Genes.

BACKGROUND: The clinical value of pyroptosis-related genes (PRGs) in lung adenocarcinoma (LUAD) remains obscure. OBJECTIVE: The study attempts to explore PRGs in LUAD, which will enable an understanding of LUAD from the perspective of PRGs. METHODS: Lung adenocarcinoma patients were diagnosed using pathology, and their clinical information was collected from several public databases. A PRGs prognostic signature (PPS) for LUAD patients was established based on a multivariate Cox regression analysis. The differential expression of PRGs was identified using standardized mean differences in 6,958 samples. The area under the curve (AUC) was used to evaluate the predictive effects of the PPS to determine the survival rate of LUAD patients. Decision curve analysis was utilized to assess the clinical significance of the PPS in LUAD. RESULTS: The PPS consists of five PRGs, namely CASP3, CASP9, GSDMB, NLRP1, and TNF. The prognostic effect of the PPS is evident in all the predicted one-, three-, and five-year survival rates (AUCs ≥ 0.58). The PPS represents an independent risk factor for the prognosis of LUAD patients (hazard ratio > 1; 95% confidence interval excluding 1). The PPS risk score can predict the prognosis of LUAD patients more accurately than PRGs of the PPS and multiple clinical parameters, such as age, tumor stage, and clinical stage. The decision curve analysis revealed that the nomogram based on the PPS and clinical parameters might result in better clinical decisions. CONCLUSION: The PPS makes it feasible to distinguish LUAD from non-LUAD. Thus, the underlying significance of the PPS in distinguishing LUAD from non-LUAD is promising.

A Novel 5-Methylcytosine- and Immune-Related Prognostic Signature Is a Potential Marker of Idiopathic Pulmonary Fibrosis.

Idiopathic pulmonary fibrosis (IPF) is the most common and highly lethal pulmonary interstitial lung disease. The current study is aimed at investigating reliable markers suitable for the treatment and identification of IPF. This study constructed the first 5-methylcytosine- (m5C-) and immune-related prognostic signature (m5CPS) based on coexpressed genes of m5C regulatory genes and immune-related genes. The m5CPS was established using the training cohort (n = 68) and verified using the test (n = 44) and validation (n = 64) cohorts. The area under the curve (AUC) values were utilized to evaluate the accuracy of m5CPS in predicting the survival of IPF patients. The Kaplan-Meier curves and Cox regression analyses were used to assess the prognostic effect of m5CPS. The AUC was utilized to evaluate the reliability of m5CPS in distinguishing IPF patients from healthy individuals. In terms of the results, m5CPS could predict the one-, three-, and five-year survival rates of IPF patients with high accuracy (AUC = .803-.973). In fact, m5CPS is not only an independent indicator of the poor prognosis of IPF patients (hazard ratio > 1; p < .05) but can also distinguish IPF patients from healthy individuals (AUC = .862). Also, m5CPS may affect the immune response and inflammatory response, and it was positively associated with the infiltration levels of active mast cells (p < .05). In sum, the current study establishes a novel m5CPS for IPF and reveals the role of m5CPS as a reliable marker for predicting the prognosis and disease status of IPF patients.

The clinical significance of integrin subunit alpha V in cancers: from small cell lung carcinoma to pan-cancer.

BACKGROUND: Little is known about the relationship between integrin subunit alpha V (ITGAV) and cancers, including small cell lung cancer (SCLC). METHODS: Using large sample size from multiple sources, the clinical roles of ITGAV expression in SCLC were explored using differential expression analysis, receiver operating characteristic curves, Kaplan-Meier curves, etc. RESULTS: Decreased mRNA (SMD = - 1.05) and increased protein levels of ITGAV were detected in SCLC (n = 865). Transcription factors-ZEB2, IK2F1, and EGR2-may regulate ITGAV expression in SCLC, as they had ChIP-Seq (chromatin immunoprecipitation followed by sequencing) peaks upstream of the transcription start site of ITGAV. ITGAV expression made it feasible to distinguish SCLC from non-SCLC (AUC = 0.88, sensitivity = 0.78, specificity = 0.84), and represented a risk role in the prognosis of SCLC (p < 0.05). ITGAV may play a role in cancers by influencing several immunity-related signaling pathways and immune cells. Further, the extensive pan-cancer analysis verified the differential expression of ITGAV and its clinical significance in multiple cancers. CONCLUSION: ITGAV served as a potential marker for prognosis and identification of cancers including SCLC.

Clinical significance of cyclin-dependent kinase inhibitor 2C expression in cancers: from small cell lung carcinoma to pan-cancers.

BACKGROUND: Cyclin-dependent kinase inhibitor 2C (CDKN2C) was identified to participate in the occurrence and development of multiple cancers; however, its roles in small cell lung carcinoma (SCLC) remain unclear. METHODS: Differential expression analysis of CDKN2C between SCLC and non-SCLC were performed based on 937 samples from multiple centers. The prognosis effects of CDKN2C in patients with SCLC were detected using both Kaplan-Meier curves and log-rank tests. Using receiver-operating characteristic curves, whether CDKN2C expression made it feasible to distinguish SCLC was determined. The potential mechanisms of CDKN2C in SCLC were investigated by gene ontology terms and signaling pathways (Kyoto Encyclopedia of Genes and Genomes). Based on 10,080 samples, a pan-cancer analysis was also performed to determine the roles of CDKN2C in multiple cancers. RESULTS: For the first time, upregulated CDKN2C expression was detected in SCLC samples at both the mRNA and protein levels (p of Wilcoxon rank-sum test < 0.05; standardized mean difference = 2.86 [95% CI 2.20-3.52]). Transcription factor FOXA1 expression may positively regulate CDKN2C expression levels in SCLC. High CDKN2C expression levels were related to the poor prognosis of patients with SCLC (hazard ratio > 1, p < 0.05) and showed pronounced effects for distinguishing SCLC from non-SCLC (sensitivity, specificity, and area under the curve ≥ 0.95). CDKN2C expression may play a role in the development of SCLC by affecting the cell cycle. Furthermore, the first pan-cancer analysis revealed the differential expression of CDKN2C in 16 cancers (breast invasive carcinoma, etc.) and its independent prognostic significance in nine cancers (e.g., adrenocortical carcinoma). CDKN2C expression was related to the immune microenvironment, suggesting its potential usefulness as a prognostic marker in immunotherapy. CONCLUSIONS: This study identified upregulated CDKN2C expression and its clinical significance in SCLC and other multiple cancers, suggesting its potential usefulness as a biomarker in treating and differentiating cancers.

SYNJ2 is a novel and potential biomarker for the prediction and treatment of cancers: from lung squamous cell carcinoma to pan-cancer.

BACKGROUND: The roles and clinical values of synaptojanin 2 (SYNJ2) in lung squamous cell carcinoma (LUSC) remain unclear. METHODS: A total of 2824 samples from multi-center were collected to identify the expression of SYNJ2 in LUSC by using Wilcoxon rank-sum test, t-test, and standardized mean difference (SMD), and 194 in-house samples were also included to validate SYNJ2 expression in LUSC. The clinical roles of SYNJ2 were investigated via receiver operating characteristic (ROC) curves, univariate Cox regression analysis, and Kaplan-Meier plots. The underlying mechanisms of SYNJ2 in LUSC were explored by gene set enrichment analysis and immune correlation analysis. Further, a pan-cancer analysis based on 10,238 sapiens was performed to promote the understating of the expression and clinical significance of SYNJ2 in multiple human cancers. RESULTS: SYNJ2 was found to be significantly upregulated in LUSC at both mRNA and protein levels (p < 0.05, SMD = 0.89 [95% CI 0.34-1.45]) via public and in-house samples. Overexpressed SYNJ2 predicted poor prognosis for LUSC patients (hazard ratio = 2.38 [95% CI 1.42-3.98]). The cancer-promoting effect of SYNJ2 may be related to protein digestion and absorption and extracellular matrix-receptor interaction. SYNJ2 expression was closely related to immune cell infiltration, indicating its role in the immune response. Moreover, the distinct expression levels and essential clinical relevance of SYNJ2 in a series of cancers were initially revealed in this study. CONCLUSIONS: This study disclosed the clinical significance of SYNJ2 in LUSC and multiple cancers, demonstrating the novel and potential biomarker for predicting and treating cancers.

Expression Landscape and Functional Roles of HOXA4 and HOXA5 in Lung Adenocarcinoma.

BACKGROUND: The role of HOXA family genes in the occurrence and progression of a variety of human cancers has been scatteredly reported. However, there is no systematic study on the differential expression, prognostic significance and potential molecular mechanism of HOXA4 and HOXA5 in LUAD. METHODS: In-house immunohistochemistry (IHC), multi-center microarrays, RT-qPCR and RNA-seq data were incorporated for comprehensively evaluating the expression and prognostic value of HOXA4 and HOXA5 in LUAD. The mechanism of HOXA4 and HOXA5 in the formation and development of LUAD was analyzed from multiple aspects of immune correlations, upstream transcriptional regulation, functional states of single cells and co-expressed gene network. The functional roles of HOXA4 and HOXA5 in LUAD were validated by in vitro experiments. RESULTS: As a result, in 3201 LUAD samples and 2494 non-cancer lung samples, HOXA4 and HOXA5 were significantly downexpressed (P < 0.05). The aberrant expression of HOXA5 was significantly correlated with the clinical progression of LUAD (P < 0.05). HOXA5 showed remarkable prognostic value for LUAD patients (P < 0.05). The expression of HOXA4 and HOXA5 in LUAD were negatively correlated with tumor purity and positively correlated with the infiltration of various immune cells such as B cells, T cells and macrophages. HOXA4 and HOXA5 overexpression had notable inhibitory effect on the proliferation, migration and invasion of LUAD cells. CONCLUSIONS: In conclusion, the identified downexpressed HOXA4 and HOXA5 had significant distinguishing ability for LUAD samples and affected the cellular functions of LUAD cells. The low expression of HOXA5 indicated worse overall survival of LUAD patients. Therefore, the two HOXA family genes especially HOXA5 may serve as potential biomarkers for LUAD.

Ogt Demonstrated Conspicuous Clinical Significance in Cancers, from Pan-Cancer to Small-Cell Lung Cancer.

The clinical progression of small-cell lung cancer (SCLC) remains pessimistic. The aim of the present study was to promote the understanding of the clinical significance and mechanism of O-linked N-acetylglucosamine (GlcNAc) transferase (OGT) in SCLC. Wilcoxon tests, standardized mean difference (SMD), and Kruskal-Wallis tests were utilized to compare OGT level differences among the experimental and control groups. The univariate Cox regression analysis, Kaplan-Meier curves, and receiver operating characteristic curves were applied to determine OGT's clinical relevance in cancers. The Spearman correlation analysis and enrichment analysis were utilized to explore the underlying mechanisms of OGT in cancers. For the first time in the field, we provide an overview of OGT in 32 cancers using a large number of samples (n = 21,196), determining distinct OGT expression in 25 cancers and its prognosis effects in 12 cancers. Furthermore, using 950 samples from multiple sources, upregulated OGT was found in both mRNA and protein levels in SCLC (SMD = 0.93, 95% CI [0.24, 1.63]). Higher OGT levels represented a more unfavorable disease-free interval for SCLC patients (p < 0.001). The research also identified OGT expression as a potential marker for SCLC prediction (sensitivity = 0.79, specificity = 0.86, and AUC = 0.88). The high expression of OGT in SCLC may result from the positive regulation of two transcription factors-DEK and XRN2. We primarily investigated the underlying mechanisms of OGT in SCLC. Herein, based on the analyses from pan-cancer to SCLC, OGT demonstrated conspicuous clinical significance. OGT may be an underlying biomarker for the treatment and identification of some cancers, including SCLC.

Prognostic signature of esophageal adenocarcinoma based on pyroptosis-related genes.

BACKGROUND: The role of pyroptosis-related genes (PRGs) in esophageal adenocarcinoma (EAC) remains unknown. METHODS: In this study, the first PRGs prognostic signature (PPS) of EAC was constructed based on the results of multivariate stepwise Cox regression analysis. Based on 1,047 samples of EAC and normal esophagus (NE), differentially expressed PRGs were selected for the establishment of the PPS. The discrimination effect of this PPS was detected by receiver operating characteristic curves, and the prognosis value of this PPS was determined through Cox regression analysis and Kaplan-Meier curves. Net benefits of the EAC patients from the nomogram (constructed based on the PPS and some clinical parameters) were assessed via decision curve analysis. The potential molecular mechanism of the PPS in EAC was explored via gene set enrichment analysis. The ability of PPS to distinguish EAC and NE was evaluated based on the results of summary receiver operating characteristic curves. RESULTS: The significant prognostic value of PPS can be observed at all of the training cohort, test cohort, and validation cohort, such as its independent risk role in the prognosis of the EAC patients (hazard ratio > 0; 95% CI not including 0). The positive net benefits of the nomogram for the EAC patients can be detected via decision curve analysis, and the potential molecular mechanism of the PPS in EAC is likely related to cell pyroptosis. Last, some of the PRGs (particularly CASP5) included in this PPS specifically support its feasibility for identifying EAC (area under the curves > 0.7). CONCLUSIONS: The construction of this PPS in EAC enhances the present understanding of the relationship between PRGs and EAC, thus representing a novel approach to the clinical identification and management of EAC based on PRGs.